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Author(s):  
Gabriel Soares Campos ◽  
Fernando Flores Cardoso ◽  
Claudia Cristina Gulias Gomes ◽  
Robert Domingues ◽  
Luciana Correia de Almeida Regitano ◽  
...  

Abstract Genomic prediction has become the new standard for genetic improvement programs, and currently, there is a desire to implement this technology for the evaluation of Angus cattle in Brazil. Thus, the main objective of this study was to assess the feasibility of evaluating young Brazilian Angus (BA) bulls and heifers for 12 routinely recorded traits using single-step genomic BLUP (ssGBLUP) with and without genotypes from American Angus (AA) sires. The second objective was to obtain estimates of effective population size (Ne) and linkage disequilibrium (LD) in the Brazilian Angus population. The dataset contained phenotypic information for up to 277,661 animals belonging to the Promebo® breeding program, pedigree for 362,900, of which 1,386 were genotyped for 50k, 77k, and 150k SNP panels. After imputation and quality control, 61,666 SNP were available for the analyses. In addition, genotypes from 332 American Angus (AA) sires widely used in Brazil were retrieved from the AA Association database to be used for genomic predictions. Bivariate animal models were used to estimate variance components, traditional EBV, and genomic EBV (GEBV). Validation was carried out with the linear regression method (LR) using young-genotyped animals born between 2013 and 2015 without phenotypes in the reduced dataset and with records in the complete dataset. Validation animals were further split into progeny of BA and AA sires to evaluate if their progenies would benefit by including genotypes from AA sires. The Ne was 254 based on pedigree and 197 based on LD, and the average LD (±SD) and distance between adjacent SNPs across all chromosomes was 0.27 (±0.27) and 40743.68 bp, respectively. Prediction accuracies with ssGBLUP outperformed BLUP for all traits, improving accuracies by, on average, 16% for BA young bulls and heifers. The GEBV prediction accuracies ranged from 0.37 (total maternal for weaning weight and tick count) to 0.54 (yearling precocity) across all traits, and dispersion (LR coefficients) fluctuated between 0.92 and 1.06. Inclusion of genotyped sires from the AA improved GEBV accuracies by 2%, on average, compared to using only the BA reference population. Our study indicated that genomic information could help to improve GEBV accuracies and hence genetic progress in the Brazilian Angus population. The inclusion of genotypes from American Angus sires heavily used in Brazil just marginally increased the GEBV accuracies for selection candidates.


2021 ◽  
Vol 5 (2) ◽  
pp. 52-61
Author(s):  
Yi-Ting Cheng ◽  
Sharifah-Nany Rahayu-Karmilla Syed-Hassan ◽  
Padillah Yahya ◽  
Azian Harun ◽  
Nazihah Mohd Yunus ◽  
...  

Background: Inference of genetic ancestry is of great interest in many fields and one of the markers in these analyses is ancestry informative marker single nucleotide polymorphisms (AIMSNPs). The Malay population is an ethnic group located mainly in South East Asia and comprises the largest ethnicity in Malaysia. Objectives: To determine Malay ancestry, Yahya et al, 2017 selected 37,487 SNPs from the genotyping data collected by the Malaysian Node of the Human Variome Project and Singapore Genome Variation Project and referenced them against the data from the International HapMap Project Phase 3. The SNPs determined to be informative for ancestry were compiled into AIM-SNP panels, and from these a few SNPs were selected for optimization in preparation for single base extension reaction multiplexing. Methodology: The chosen AIMSNPs were optimized and validated on Malay and non-Malay populations. Genotyping was carried out on participants of self-reported Malay and non-Malay ancestry respectively and the data were compared for Malay and non-Malay population to investigate for significant differences in the genotype between Malay and non-Malay participants. Findings: The results showed great similarities between the Malay and non-Malay population, which may arise from many factors, and further optimization of more SNPs and genotyping is required to definitively conclude the validity of the AIM-SNP panels for Malay population Conclusion: Knowledge of ancestry is important to minimise spurious association. This pilot study gives a brief account of the optimization process and offers an insight into how this may be done in South East Asian populations.


2021 ◽  
Author(s):  
Henrique Alberto Mulim ◽  
Luiz F. Brito ◽  
Luís Fernando Batista Pinto ◽  
José Bento Sterman Ferraz ◽  
Lais Grigoletto ◽  
...  

Abstract Background: A decline in the level of genetic diversity can result in reduced response to selection, greater incidence of genetic defects, and inbreeding depression. In this context, some metrics have been proposed to assess the levels of populational genetic diversity in selected populations. The main goals of this study were to: 1) investigate the population structure of 16 cattle populations from 15 different pure breeds or composite populations, which have been selected for different breeds goals; and, 2) identify and compare runs of homozygosity (ROH) and heterozygosity-enriched regions (HER) based on different single nucleotide polymorphism (SNP) panels and whole-genome sequence data (WGS), followed by functional genomic analyses. Results: A total of 24,187 ROH were found across all cattle populations, with 55% classified in the 2-4 Mb size group. Fourteen homozygosity islands were found in five populations, where four islands located on BTA1, BTA5, BTA16, and BTA19 overlapped between the Brahman (BRM) and Gyr (GIR) breeds. A functional analysis of the genes found in these islands revealed candidate genes known to play a role in the melanogenesis, prolactin signaling, and calcium signaling pathways. The correlations between inbreeding metrics ranged from 0.02 to 0.95, where the methods based on homozygous genotypes (FHOM), uniting of gametes (FUNI), and genotype additive variance (FGRM) showed strong correlations among them. All methods yielded low to moderate correlations with the inbreeding coefficients based on runs of homozygosity (FROH). For the HER, 3,576 runs and 26 islands, distributed across all autosomal chromosomes, were found in regions containing genes mainly related to the immune system. Although the analyses with WGS did not enable detection of the same island patterns, it unraveled novel regions not captured when using SNP panel data.Conclusions: The cattle populations that showed the largest amount of ROH and HER were Senepol (SEN) and Montana (MON), respectively. Overlapping ROH islands were identified between GIR and BRM breeds, indicating a possible historical connection between the populations. The distribution and pattern of ROH and HER are population specific, indicating that different breeds have experienced divergent selection processes or different genetic processes.


2021 ◽  
Author(s):  
Paul Flynn ◽  
Romy Morrin-O'Donnell ◽  
Rebecca Weld ◽  
Laura M Gargan ◽  
Jens Carlsson ◽  
...  

Short tandem repeat (STR), also known as microsatellite markers are currently used for genetic parentage verification within equine. Transitioning from STR to single nucleotide polymorphism (SNP) markers to perform equine parentage verification is now a potentially feasible prospect and a key area requiring evaluation is parentage testing accuracies when using SNP based methods, in comparison to STRs. To investigate, we utilised a targeted equine genotyping by sequencing (GBS) panel of 562 SNPs to SNP genotype 309 Thoroughbred horses - inclusive of 55 previously parentage verified offspring. Availability of STR profiles for all 309 horses, enabled comparison of parentage accuracies between SNP and STR panels. An average sample call rate of 97.2% was initially observed, and subsequent removal of underperforming SNPs realised a pruned final panel of 516 SNPs. Simulated trio and partial parentage scenarios were tested across 12-STR, 16-STR, 147-SNP and 516-SNP panels. False-positives (i.e. expected to fail parentage, but pass) ranged from 0% for 147-SNP and 516-SNP panels to 0.003% when using 12-STRs within trio parentage scenarios, and 0% for 516-SNPs to 1.6% for 12-STRs within partial parentage scenarios. Our study leverages targeted GBS methods to generate low-density equine SNP profiles and demonstrates the value of SNP based equine parentage analysis in comparison to STRs - particularly when performing partial parentage discovery.


Author(s):  
Zhendong Gao ◽  
Yuebo Zhang ◽  
Zhi Li ◽  
Qinhua Zeng ◽  
Fang Yang ◽  
...  
Keyword(s):  

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1992
Author(s):  
Duanyang Ren ◽  
Jinyan Teng ◽  
Shuqi Diao ◽  
Qing Lin ◽  
Jiaqi Li ◽  
...  

With the availability of high-density single-nucleotide polymorphism (SNP) data and the development of genotype imputation methods, high-density panel-based genomic prediction (GP) has become possible in livestock breeding. It is generally considered that the genomic estimated breeding value (GEBV) accuracy increases with the marker density, while studies have shown that the GEBV accuracy does not increase or even decrease when high-density panels were used. Therefore, in addition to the SNP number, other measurements of ‘marker density’ seem to have impacts on the GEBV accuracy, and exploring the relationship between the GEBV accuracy and the measurements of ‘marker density’ based on high-density SNP or whole-genome sequence data is important for the field of GP. In this study, we constructed different SNP panels with certain SNP numbers (e.g., 1 k) by using the physical distance (PhyD), genetic distance (GenD) and random distance (RanD) between SNPs respectively based on the high-density SNP data of a Germany Holstein dairy cattle population. Therefore, there are three different panels at a certain SNP number level. These panels were used to construct GP models to predict fat percentage, milk yield and somatic cell score. Meanwhile, the mean (d¯) and variance (σd2) of the physical distance between SNPs and the mean (r2¯) and variance (σr22) of the genetic distance between SNPs in each panel were used as marker density-related measurements and their influence on the GEBV accuracy was investigated. At the same SNP number level, the d¯ of all panels is basically the same, but the σd2, r2¯ and σr22 are different. Therefore, we only investigated the effects of σd2, r2¯ and σr22 on the GEBV accuracy. The results showed that at a certain SNP number level, the GEBV accuracy was negatively correlated with σd2, but not with r2¯ and σr22. Compared with GenD and RanD, the σd2 of panels constructed by PhyD is smaller. The low and moderate-density panels (< 50 k) constructed by RanD or GenD have large .σd2., which is not conducive to genomic prediction. The GEBV accuracy of the low and moderate-density panels constructed by PhyD is 3.8~34.8% higher than that of the low and moderate-density panels constructed by RanD and GenD. Panels with 20–30 k SNPs constructed by PhyD can achieve the same or slightly higher GEBV accuracy than that of high-density SNP panels for all three traits. In summary, the smaller the variation degree of physical distance between adjacent SNPs, the higher the GEBV accuracy. The low and moderate-density panels construct by physical distance are beneficial to genomic prediction, while pruning high-density SNP data based on genetic distance is detrimental to genomic prediction. The results provide suggestions for the development of SNP panels and the research of genome prediction based on whole-genome sequence data.


Genome ◽  
2021 ◽  
Author(s):  
Alejandra Maria Toro Ospina ◽  
Ignacio Aguilar ◽  
Matheus Henrique Vargas de Oliveira ◽  
Luiz eduardo Cruz dos Santos Correia ◽  
Anibal Eugenio Vercesi Filho ◽  
...  

The objective of this study was to evaluate the accuracy of imputation in a Gyr population using two medium density panels (Bos taurus - Bos indicus) and to test whether the inclusion of the Nellore breed increases the imputation accuracy in the Gyr population. The database consisted of 289 Gyr females from Brazil genotyped with the GGP Bovine LDv4 chip containing 30,000 SNPs and 158 Gyr females from Colombia genotyped with the GGP indicus chip containing 35,000 SNPs. A customized chip was created that contained the information of 9,109 SNPs (9K) to test the imputation accuracy in Gyr populations; 604 Nellore animals with information of LD SNPs tested in the scenarios were included in the reference population. Four scenarios were tested: LD9K_30KGIR, LD9K_35INDGIR, LD9K_30KGIR_NEL and LD9K_35INDGIR_NEL. Principal component analysis (PCA) was computed for the genomic matrix and sample-specific imputation accuracies were calculated using Pearson’s correlation (CS) and the concordance rate (CR) for imputed genotypes. The results of PCA of the Colombian and Brazilian Gyr populations demonstrated the genomic relationship between the two populations. The CS and CR ranged from 0.88 to 0.94 and from 0.93 to 0.96, respectively. Among the scenarios tested, the highest CS (0.94) was observed for the LD9K_30KGIR scenario.However, the variation in SNPs may reduce the imputation accuracy even when the chip of the Bos indicus subspecies is used


2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Jinghui Li ◽  
Zigui Wang ◽  
Rohan Fernando ◽  
Hao Cheng

AbstractDense single nucleotide polymorphism (SNP) panels are widely used for genome-wide association studies (GWAS). In these panels, SNPs within a genomic segment tend to be highly correlated. Thus, association studies based on testing the significance of single SNPs are not very effective, and genomic-window based tests have been proposed to address this problem. However, when the SNP density on the genotype panel is not homogeneous, genomic-window based tests can lead to the detection of spurious associations by declaring effects of genomic windows that explain a large proportion of genetic variance as significant. We propose two methods to solve this problem.


Author(s):  
Soyeon Bae ◽  
Sohyoung Won ◽  
Heebal Kim

AbstractDue to the advantages of single-nucleotide polymorphisms (SNPs) in forensic science, many forensic SNP panels have been developed. However, the existing SNP panels have a problem that they do not reflect allele frequencies in Koreans or the number of markers is not sufficient to perform paternity testing. Here, we filtered candidate SNPs from the Ansan-Ansung cohort data and selected 200 SNPs with high allele frequencies. To reduce the risk of false inclusion and false exclusion, we calculated likelihood ratios of alleged father-child pairs from simulated families when the alleged father is the true father, the close relative of the true father, and the random man. As a result, we estimated that 160 SNPs were needed to perform paternity testing. Furthermore, we performed validation using Twin-Family cohort data. When 160 selected SNPs were used to calculate the likelihood ratio, paternity and non-paternity were accurately distinguished. Our set of 160 SNPs could be useful for paternity testing in Koreans.


2021 ◽  
Vol 12 ◽  
Author(s):  
Rachel P. Naegele ◽  
Jeff DeLong ◽  
Safa A. Alzohairy ◽  
Seiya Saito ◽  
Noor Abdelsamad ◽  
...  

As sequencing costs continue to decrease, new tools are being developed for assessing pathogen diversity and population structure. Traditional marker types, such as microsatellites, are often more cost effective than single-nucleotide polymorphism (SNP) panels when working with small numbers of individuals, but may not allow for fine scale evaluation of low or moderate structure in populations. Botrytis cinerea is a necrotrophic plant pathogen with high genetic variability that can infect more than 200 plant species worldwide. A panel of 52 amplicons were sequenced for 82 isolates collected from four Michigan vineyards representing 2 years of collection and varying fungicide resistance. A panel of nine microsatellite markers previously described was also tested across 74 isolates from the same population. A microsatellite and SNP marker analysis of B. cinerea populations was performed to assess the genetic diversity and population structure of Michigan vineyards, and the results from both marker types were compared. Both methods were able to detect population structure associated with resistance to the individual fungicides thiabendazole and boscalid, and multiple fungicide resistance (MFR). Microsatellites were also able to differentiate population structure associated with another fungicide, fluopyram, while SNPs were able to additionally differentiate structure based on year. For both methods, AMOVA results were similar, with microsatellite results explaining a smaller portion of the variation compared with the SNP results. The SNP-based markers presented here were able to successfully differentiate population structure similar to microsatellite results. These SNP markers represent new tools to discriminate B. cinerea isolates within closely related populations using multiple targeted sequences.


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